Re: [Numpy-discussion] Integers to negative integer powers, time for a decision.

Well, testing under windows 64 bit, Python 3.5.2, positive powers of integers give integers and negative powers of integers give floats. So, do you want to raise an exception when taking a negative power of an element of an array of integers? Because not doing so would be inconsistent with

Re: [Numpy-discussion] Integers to negative integer powers, time for a decision.

Hi all, Just to have the options clear. Is the operator '**' going to be handled in any different manner than pow? Thanks. Armando ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] Integers to integer powers, let's make a decision

Also in favor of 2. Always return a float for '**' On 04.06.2016 21:47, josef.p...@gmail.com wrote: On Sat, Jun 4, 2016 at 3:43 PM, Charles R Harris wrote: On Sat, Jun 4, 2016 at 11:22 AM, Charles R Harris wrote: Hi All, I've made a

Re: [Numpy-discussion] Best way to expose std::vector to be used with numpy

On 15.10.2014 21:48, Chris Barker wrote: Sorry about SWIG -- maybe a chance to move on ;-) I'd go with Cython -- this is pretty straightforward, and it handles the buffer protocol for you under the hood. +1 All the standard containers are automatically wrapped and C++ exceptions can be

Re: [Numpy-discussion] [JOB ANNOUNCEMENT] Software Developer permanent position

On 21.02.2014 10:55, David Goldsmith wrote: On Thu, Feb 20, 2014 at 10:37 PM, wrote: Date: Fri, 21 Feb 2014 07:43:17 +0100 From: V. Armando Sol? *Ref. 8173* *- Deadline for returning application forms: * *01/04/2014* I assume thats the European date format, i.e., the due date is April

[Numpy-discussion] [JOB ANNOUNCEMENT] Software Developer permanent position available at ESRF, France

Dear colleagues, The ESRF is looking for a Software Developer: http://esrf.profilsearch.com/recrute/fo_annonce_voir.php?id=300 Our ideal candidate would be experienced on OpenGL, OpenCL and Python. Best regards, Armando ___ NumPy-Discussion mailing

Re: [Numpy-discussion] [JOB ANNOUNCEMENT] Software Developer permanent position available at ESRF, France

Sorry, the link was in French ... The English version: http://esrf.profilsearch.com/recrute/fo_form_cand.php?_lang=enid=300 Best regards, Armando On 20.02.2014 18:21, V. Armando Sole wrote: Dear colleagues, The ESRF is looking for a Software Developer: http://esrf.profilsearch.com

Re: [Numpy-discussion] Windows, blas, atlas and dlls

On 22.02.2013 19:54, Sergio Callegari wrote: from scipy.linalg.blas import fblas dgemm = fblas.dgemm._cpointer sgemm = fblas.sgemm._cpointer OK, but this gives me a PyCObject. How do I make it a function pointer of the correct type in cython? In cython I do not know it. I coded it

Re: [Numpy-discussion] Windows, blas, atlas and dlls

On 18.02.2013 21:23, Pauli Virtanen wrote: 18.02.2013 20:41, Dag Sverre Seljebotn kirjoitti: [clip] I think there should be a new project, pylapack or similar, for this, outside of NumPy and SciPy. NumPy and SciPy could try to import it, and if found, fetch a function pointer table. (If

Re: [Numpy-discussion] Windows, blas, atlas and dlls

On 18.02.2013 22:47, Pauli Virtanen wrote: 18.02.2013 23:29, V. Armando Sole kirjoitti: [clip] I find Dag's approach more appealing. SciPy can be problematic (windows 64-bit) and if one could offer access to the linear algebra functions without needing SciPy I would certainly prefer

Re: [Numpy-discussion] (2012) Accessing LAPACK and BLAS from the numpy C API

Hi Sturla, Quoting Sturla Molden stu...@molden.no: Den 10.03.2012 22:56, skrev Sturla Molden: I am not sure why NumPy uses f2c'd routines instead of a dependency on BLAS and LAPACK like SciPy. Actually, np.dot does depend on the CBLAS interface to BLAS (_dotblas.c). But the lapack

Re: [Numpy-discussion] Long-standing issue with using numpy in embedded CPython

Quoting Robert Kern robert.k...@gmail.com: On Fri, Dec 9, 2011 at 11:00, Yang Zhang yanghates...@gmail.com wrote: Thanks for the clarification.  Alas.  So is there no simple workaround to making numpy work in environments such as Jepp? I don't think so, no. It is far from being an optimal

Re: [Numpy-discussion] what python module to modify NetCDF data?

Hi, I have never seen myself a NetCDF file but if your NetCDF file is using HDF5 as format (possible since NetCDF 4 if I am not mistaken), you should be able to use h5py or PyTables to access and or modify it. Best regards, Armando Quoting Chao YUE chaoyue...@gmail.com: Dear all, I

Re: [Numpy-discussion] Simple problem. Is it possible without a loop?

Correct. I thought just multiplying by -1 and inverting the logical condition would give me the same output. This makes exactly what I want: x= numpy.arange(10.) delta=3 y=[x[0]] for value in x: ... if (value-y[-1]) delta: ...y.append(value) ... y [0., 4., 8.] Armando

Re: [Numpy-discussion] Simple problem. Is it possible without a loop?

? Well a loop or list comparison seems like a good choice to me. It is much more obvious at the expense of two LOCs. Did you profile the two possibilities and are they actually performance-critical? cheers The second is between 8 and ten times faster on my machine. import numpy import

Re: [Numpy-discussion] Simple problem. Is it possible without a loop?

. Armando Quoting Vicente Sole s...@esrf.fr: ? Well a loop or list comparison seems like a good choice to me. It is much more obvious at the expense of two LOCs. Did you profile the two possibilities and are they actually performance-critical? cheers The second is between 8 and ten times

Re: [Numpy-discussion] Simple problem. Is it possible without a loop?

Quoting josef.p...@gmail.com: but the two options don't produce the same result in general, the cumsum version doesn't restart from zero, I think try x0 = np.random.randint(5,size=30).cumsum() with delta=3 I don't see a way around recursive looping The x0 data are already sorted. It was

Re: [Numpy-discussion] Matrix operation.

With A and X being arrays: B=numpy.zeros(A.shape, A.dtype) B[A0] = X Armando Quoting gerardob gberbeg...@gmail.com: Let A be a square matrix of 0's and 1's, and let X be a one dimesional vector. The length of X is equal to the number of 1's that A has. I would like to produce a new

Re: [Numpy-discussion] performance matrix multiplication vs. matlab

Quoting Bruce Southey bsout...@gmail.com: On 01/18/2010 12:47 PM, Vicente Sole wrote: Quoting Bruce Southey bsout...@gmail.com: If you obtain the code from any package then you are bound by the terms of that code. So while a user might not be 'inconvenienced' by the LGPL, they are required

Re: [Numpy-discussion] Numpy unexpected (for me) behaviour

At 01:44 23/01/2009 -0600, Robert Kern wrote: It is an inevitable consequence of several features interacting together. Basically, Python expands a[b] += 1 into this: c = a[b] d = c.__iadd__(1) a[b] = d Basically, the array c doesn't know that it was created by indexing a, so it can't

[Numpy-discussion] Numpy unexpected (for me) behaviour

Hello, In an effort to suppress for loops, I have arrived to the following situation. Through vectorial logical operations I generate a set of indices for which the contents of an array have to be incremented. My problem can be reduced to the following: #This works import numpy